
Programowanie w jezyku R
door
Marek Gagolewski
Nog geen beoordelingen
Business & Economics
Formaat
Paperback
Pagina's
550
Taal
Pools
Gepubliceerd
Jan 1, 2016
Uitgever
Wydawnictwo Naukowe PWN
ISBN-10
8301189398
ISBN-13
9788301189396
Beschrijving
Marek Gagolewski presents a comprehensive guide to programming in R, an increasingly popular language among data scientists and statisticians. He delves into the strengths of R as a tool for statistical analysis and visualization, making it accessible for both novices and experienced programmers.
The author systematically explores key concepts, starting with the basics and gradually introducing more complex topics, ensuring that readers can build a solid foundation in R programming. Gagolewski employs clear explanations, practical examples, and engaging exercises to solidify the learner's understanding, making the nuances of R approachable and intriguing.
Readers will appreciate the focus on real-world applications of R, as Gagolewski shares insights into data manipulation, graphical representation, and statistical modeling. This practical approach emphasizes not just the "how" but also the "why," cultivating a deeper appreciation for data analysis techniques.
By combining theory with practice, Gagolewski empowers readers to harness the full potential of R, enabling them to tackle their own data challenges with confidence. This book serves as a valuable resource for anyone looking to enhance their programming skills and apply data science principles effectively.
The author systematically explores key concepts, starting with the basics and gradually introducing more complex topics, ensuring that readers can build a solid foundation in R programming. Gagolewski employs clear explanations, practical examples, and engaging exercises to solidify the learner's understanding, making the nuances of R approachable and intriguing.
Readers will appreciate the focus on real-world applications of R, as Gagolewski shares insights into data manipulation, graphical representation, and statistical modeling. This practical approach emphasizes not just the "how" but also the "why," cultivating a deeper appreciation for data analysis techniques.
By combining theory with practice, Gagolewski empowers readers to harness the full potential of R, enabling them to tackle their own data challenges with confidence. This book serves as a valuable resource for anyone looking to enhance their programming skills and apply data science principles effectively.
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